{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# if ImportError: dlopen: cannot load any more object with static TLS occurs.\n",
    "# maybe you should import Dataset, DataLoader modules first\n",
    "from torch.utils.data import Dataset, DataLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import reload when you need to modify the modules\n",
    "from imp import reload"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import supNet\n",
    "reload(supNet)\n",
    "supNet.supNet()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the total of data is 60000\n",
      "the number of sample:  7120\n",
      "Done.\n",
      "the number of sample:  52880\n",
      "Done.\n",
      "the number of sample:  10000\n",
      "Done.\n",
      "Train[1 / 500] loss: 0.63498, Acc: 5.59\n",
      "Train[2 / 500] loss: 0.58010, Acc: 11.67\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train[192 / 500] loss: 0.00069, Acc: 28.09\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Train[500 / 500] loss: 0.00001, Acc: 28.09\n",
      "Test: Loss: 0.22499, Acc: 95.67 %\n",
      "Accuracy of     0 : 98 %\n",
      "Accuracy of     1 : 98 %\n",
      "Accuracy of     2 : 94 %\n",
      "Accuracy of     3 : 94 %\n",
      "Accuracy of     4 : 95 %\n",
      "Accuracy of     5 : 94 %\n",
      "Accuracy of     6 : 96 %\n",
      "Accuracy of     7 : 93 %\n",
      "Accuracy of     8 : 94 %\n",
      "Accuracy of     9 : 93 %\n"
     ]
    }
   ],
   "source": [
    "import SemisupNet\n",
    "reload(SemisupNet)\n",
    "SemisupNet.SemisupNet()"
   ]
  }
 ],
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